Open Access Methodology article

Combined genotype and haplotype tests for region-based association studies

Sergii Zakharov12*, Tien Yin Wong34, Tin Aung34, Eranga Nishanthie Vithana3, Chiea Chuen Khor12, Agus Salim2 and Anbupalam Thalamuthu15*

Author Affiliations

1 Human Genetics, Genome Institute of Singapore, Singapore, Singapore

2 Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

3 Singapore Eye Research Institute, Singapore, Singapore

4 Department of Ophthalmology, National University Health System, Singapore, Singapore

5 Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia

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BMC Genomics 2013, 14:569  doi:10.1186/1471-2164-14-569

Published: 21 August 2013



Although single-SNP analysis has proven to be useful in identifying many disease-associated loci, region-based analysis has several advantages. Empirically, it has been shown that region-based genotype and haplotype approaches may possess much higher power than single-SNP statistical tests. Both high quality haplotypes and genotypes may be available for analysis given the development of next generation sequencing technologies and haplotype assembly algorithms.


As generally it is unknown whether genotypes or haplotypes are more relevant for identifying an association, we propose to use both of them with the purpose of preserving high power under both genotype and haplotype disease scenarios. We suggest two approaches for a combined association test and investigate the performance of these two approaches based on a theoretical model, population genetics simulations and analysis of a real data set.


Based on a theoretical model, population genetics simulations and analysis of a central corneal thickness (CCT) Genome Wide Association Study (GWAS) data set we have shown that combined genotype and haplotype approach has a high potential utility for applications in association studies.

Genotype-based tests; Haplotype-based tests; Association analysis; Test statistic combination